25,892 research outputs found
Nuclear Modification to Parton Distribution Functions and Parton Saturation
We introduce a generalized definition of parton distribution functions (PDFs)
for a more consistent all-order treatment of power corrections. We present a
new set of modified DGLAP evolution equations for nuclear PDFs, and show that
the resummed -type of leading nuclear size enhanced power
corrections significantly slow down the growth of gluon density at small-.
We discuss the relation between the calculated power corrections and the
saturation phenomena.Comment: 4 pages, to appear in the proceedings of QM200
Dynamical properties of a trapped dipolar Fermi gas at finite temperature
We investigate the dynamical properties of a trapped finite-temperature
normal Fermi gas with dipole-dipole interaction. For the free expansion
dynamics, we show that the expanded gas always becomes stretched along the
direction of the dipole moment. In addition, we present the temperature and
interaction dependences of the asymptotical aspect ratio. We further study the
collapse dynamics of the system by suddenly increasing the dipolar interaction
strength. We show that, in contrast to the anisotropic collapse of a dipolar
Bose-Einstein condensate, a dipolar Fermi gas always collapses isotropically
when the system becomes globally unstable. We also explore the interaction and
temperature dependences for the frequencies of the low-lying collective
excitations.Comment: 11 pages, 7 figure
Role of the nonperturbative input in QCD resummed Drell-Yan -distributions
We analyze the role of the nonperturbative input in the Collins, Soper, and
Sterman (CSS)'s -space QCD resummation formalism for Drell-Yan transverse
momentum () distributions, and investigate the predictive power of the CSS
formalism. We find that the predictive power of the CSS formalism has a strong
dependence on the collision energy in addition to its well-known
dependence, and the dependence improves the predictive power
at collider energies. We show that a reliable extrapolation from perturbatively
resummed -space distributions to the nonperturbative large region is
necessary to ensure the correct distributions. By adding power
corrections to the renormalization group equations in the CSS formalism, we
derive a new extrapolation formalism. We demonstrate that at collider energies,
the CSS resummation formalism plus our extrapolation has an excellent
predictive power for and production at all transverse momenta . We also show that the -space resummed distributions provide a good
description of Drell-Yan data at fixed target energies.Comment: Latex, 43 pages including 15 figures; typos were correcte
Resummed QCD Power Corrections to Nuclear Shadowing
We calculate and resum a perturbative expansion of nuclear enhanced power
corrections to the structure functions measured in deeply inelastic scattering
of leptons on a nuclear target. Our results for the Bjorken -, - and
-dependence of nuclear shadowing in and the nuclear
modifications to , obtained in terms of the QCD factorization
approach, are consistent with the existing data. We demonstrate that the
low- behavior of these data and the measured large longitudinal structure
function point to a critical role for the power corrections when compared to
other theoretical approaches.Comment: 4 pages, 3 figures, uses RevTeX 4. As published in Phys.Rev.Let
Resummation of nuclear enhanced higher twist in the Drell Yan process
We investigate higher twist contributions to the transverse momentum
broadening of Drell Yan pairs in proton nucleus collisions. We revisit the
contribution of matrix elements of twist-4 and generalize this to matrix
elements of arbitrary twist. An estimate of the maximal nuclear broadening
effect is derived. A model for nuclear enhanced matrix elements of arbitrary
twist allows us to give the result of a resummation of all twists in closed
form. Subleading corrections to the maximal broadening are discussed
qualitatively.Comment: 10 pages, 5 figures; v2: minor changes in text, acknowledgement
added; v3: mistake in fig. 1 correcte
On several families of elliptic curves with arbitrary large Selmer groups
In this paper, we calculate the Selmer groups
S^{(\phi)} (E / \Q) and S^{(\hat{\varphi})} (E^{\prime} / \Q) of elliptic
curves via descent theory
(see [S, Chapter X]), in particular, we obtain that the Selmer groups of
several families of such elliptic curves can be arbitrary large.Comment: 22 page
Nuclear Effects on Heavy Boson Production at RHIC and LHC
We predict W and Z transverse momentum distributions from proton-proton and
nuclear collisions at RHIC and LHC. A resummation formalism with power
corrections to the renormalization group equations is used. The dependence of
the resummed QCD results on the non-perturbative input is very weak for the
systems considered. Shadowing effects are discussed and found to be unimportant
at RHIC, but important for LHC. We study the enhancement of power corrections
due to multiple scattering in nuclear collisions and numerically illustrate the
weak effects of the dependence on the nuclear mass.Comment: 21 pages, 11 figure
Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks
Multivariate time series forecasting is an important machine learning problem
across many domains, including predictions of solar plant energy output,
electricity consumption, and traffic jam situation. Temporal data arise in
these real-world applications often involves a mixture of long-term and
short-term patterns, for which traditional approaches such as Autoregressive
models and Gaussian Process may fail. In this paper, we proposed a novel deep
learning framework, namely Long- and Short-term Time-series network (LSTNet),
to address this open challenge. LSTNet uses the Convolution Neural Network
(CNN) and the Recurrent Neural Network (RNN) to extract short-term local
dependency patterns among variables and to discover long-term patterns for time
series trends. Furthermore, we leverage traditional autoregressive model to
tackle the scale insensitive problem of the neural network model. In our
evaluation on real-world data with complex mixtures of repetitive patterns,
LSTNet achieved significant performance improvements over that of several
state-of-the-art baseline methods. All the data and experiment codes are
available online.Comment: Accepted by SIGIR 201
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